Conclusions

In 2003 we started a START-funded project entitled 'Bytes for Bites: Translating Climate Forecasts into Enhanced Food Security for the Sahel' carried by a sense of 'environmental urgency' (Raynaut et al. 1997). Little did we realize then that Sudano-Sahelian farmers (and their crops) still are, in many ways, experts in resilience (Batterbury and Warren 2001; National Research Council 1996) and that our early assumption of human vulnerability could be challenged by generations of trusted kinship networks (Roncoli et al. 2001) and sophisticated practices including the selective management of plant genetic resources.

Fig. 19.4. Schematic representation of a data assimilation procedure to improve final model yield estimates using in-season rainfall forecasts and satellite biomass observations. At T =0, a crop model (mechanistic or empirical) is initialized with an ensemble of equally likely conditions (using a Monte Carlo technique). The model is then propagated forward in time with each realization of the ensemble. When estimates of system states (e.g. biomass), model parameters (crop type, sowing date, ...) or boundary conditions (cumulative rainfall) become available an Ensemble Kalman Filter (EnKF) updates these and the measures of uncertainty thereof. EnKF has improved early estimates of system states in physical oceanography, meteorology, air pollution monitoring, hydrological streamflow forecasting, petroleum engineering, fish stock assessment, and more recently carbon sequestration studies (Jones et al. 2006)

Fig. 19.4. Schematic representation of a data assimilation procedure to improve final model yield estimates using in-season rainfall forecasts and satellite biomass observations. At T =0, a crop model (mechanistic or empirical) is initialized with an ensemble of equally likely conditions (using a Monte Carlo technique). The model is then propagated forward in time with each realization of the ensemble. When estimates of system states (e.g. biomass), model parameters (crop type, sowing date, ...) or boundary conditions (cumulative rainfall) become available an Ensemble Kalman Filter (EnKF) updates these and the measures of uncertainty thereof. EnKF has improved early estimates of system states in physical oceanography, meteorology, air pollution monitoring, hydrological streamflow forecasting, petroleum engineering, fish stock assessment, and more recently carbon sequestration studies (Jones et al. 2006)

A thorough review of current knowledge on regional climate revealed that in Sudano-Sahelian West Africa, climate predictability remains limited and very likely constrains the beneficial use of current forecasts in the region. This problematic setting combines with a context of low endowment of smallscale farmers and still deficient information systems to hamper decision capacity at multiple scales by reducing the array of options available to take advantage of developing seasonal forecasting opportunities.

With this, the successful application of seasonal forecasts in Sudano-Sahelian smallholder agriculture appears today premature, contrasting with several other regions of Africa and the world, some even close (Adiku and Stone 1995) with more immediate potential.

This will change over the next decade, as progress on the implementation of retroactive land-atmosphere interactions in dynamic climate models yields tolerable uncertainty levels for uptake by Sudano-Sahelian farmers, and production systems intensify under growing population pressure, increase in sedentary agriculture and fallow reduction. Meanwhile, a range of preparatory activities can be pursued with benefits in the shorter term: the ongoing adaptation of crop models to simulate local crops and farming systems (Folliard et al. 2004), their coupling with GIS technologies to target regional breeding programs (Soumare et al. 2005), and a 'rejuvenation' of early agrometeorological crop yield assessment techniques using the latest stochastic data assimilation approaches within the rapidly expanding spectrum of data sources (Traore 2005). The latter offers timely prospects for the use of within-season, intermediate timescale forecasts in operational early warning systems and, possibly, selective response farming by Sudano-Sahelian smallholders. In a few years, progress achieved on these fronts will combine with improved predictability of climate variability trends to investigate agricultural impacts of global and regional change, and specifically the sustainability of existing and alternate patterns of adaptation (Sivakumar et al. 2005).

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